{"id":"W4406095277","doi":"10.1103/physrevd.111.023503","title":"Impact and mitigation of polarized extragalactic foregrounds on Bayesian cosmic microwave background lensing","year":2025,"lang":"en","type":"article","venue":"Physical review. D/Physical review. D.","topic":"Radio Astronomy Observations and Technology","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020 Framework Programme; Alliance de recherche numérique du Canada; H2020 European Research Council; Office of Science; University of Toronto; U.S. Department of Energy; European Commission; National Energy Research Scientific Computing Center; Lawrence Berkeley National Laboratory; Innovation, Science and Economic Development Canada; SLAC National Accelerator Laboratory; Ontario Research Foundation","keywords":"Cosmic microwave background; Physics; Estimator; Weak gravitational lensing; Astrophysics; Polarization (electrochemistry); Optics; Anisotropy; Statistics; Mathematics; Galaxy; Redshift","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002735899,0.0005085656,0.001542969,0.0001164292,0.0001573523,0.00005138178,0.0003180167,0.0000484526,0.00003591653],"category_scores_gemma":[0.00008933652,0.0004176294,0.0007436506,0.0008658472,0.0002535696,0.0003094532,0.0001092165,0.0005412903,0.00004544873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001126053,"about_ca_system_score_gemma":0.0001514705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006633085,"about_ca_topic_score_gemma":0.000001975361,"domain_scores_codex":[0.9976531,0.0002138698,0.0007289092,0.0006450876,0.000274662,0.0004843758],"domain_scores_gemma":[0.9979466,0.0004601009,0.0004842949,0.0007714541,0.0001795844,0.0001579881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006373264,0.002022489,0.09529787,0.005073122,0.0007580867,0.000002014468,0.00005045064,0.000005864116,0.0964089,0.4181267,0.0029219,0.3792689],"study_design_scores_gemma":[0.004418801,0.001666957,0.1921298,0.05111754,0.004687345,0.00001261148,0.0001159569,0.007538205,0.04654803,0.6641593,0.02489188,0.002713621],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745755,0.01076915,0.005243564,0.001695198,0.00007303944,0.001304135,0.00004585537,0.00005487488,0.006238746],"genre_scores_gemma":[0.9954396,0.002725286,0.0007103677,0.0006100413,0.0002041273,0.000110767,0.0001109922,0.0000373793,0.00005147358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3765553,"threshold_uncertainty_score":0.9998276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01414327451960683,"score_gpt":0.3926716190190657,"score_spread":0.3785283444994589,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}